Q-omics provides the consensus-scored HEXB profile across patient tissues and cancer cell-line models. HEXB expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, HEXB is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, HEXB protein abundance shows 20,378 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, HNSC, and GBM as cancer lineages where HEXB shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for HEXB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HEXB survival associations across molecular data types. HEXB RNA expression shows survival associations in the most cancer types (30), followed by mutation status (2) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HEXB RNA expression–survival associations across cancer types. High HEXB expression shows unfavorable associations in UVM, KICH, ACC, LGG, UCS and MESO. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for HEXB RNA expression.
This table summarizes HEXB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HEXB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HEXB shows lower tumor expression in LUSC and higher tumor expression in HNSC, KIRC, LIHC, KIRP and STAD. The HNSC box plot shows higher HEXB RNA expression in tumor versus normal tissue (log2 FC = +1.432, t-test p < 0.001).
This table shows molecular features associated with HEXB in patient tissues and cancer cell lines. In patient samples, HEXB shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, HEXB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BONE and UPPER_AERODIGESTIVE_TRACT.
